Single-cell cis-eQTL v1

A database of human SNP-Gene associations (eQTL)

Menu
  • eQTL project
  • Searching

Project Description

Cohort
In this project, we have 38 individuals and collected PBMC in two timepoints: before BCG vaccination and 3 months BCG vaccination. In each timepoint, the PBMCs were stimulated with/without LPS. In total, we have four conditions, Baseline BCG effect, LPS effect and BCG+LPS effect.
Analysis
We performed three analysis using different models. limix_qtl[1] was used in this project. For the Main Effect, we combined four conditions together per cell type and calculated the SNP and eGene correlation. For the Interaction Effect we add G*E as the interaction term. For the Trained Immunity Effect we focus on monocytes and calculated the correlation between SNP and gene expression changes between two conditions (BCG+LPS and LPS).
Details of eQTL
Cell-type eQTL (Left): The main effect in each cell type. In this mode, four conditions are combined to identified the main effect in each cell type. Response eQTL (Middel): BCG effect, LPS effect and LPS effect under BCG condition are calculated in each cell type. Trained Immunity eQTL (Right): Trained immunity effect is calcualted in monocytes. The gene expression difference is used as phenotype.

References

[1] https://github.com/single-cell-genetics/limix_qtl

Citation

Integrating single-cell response eQTL and multiomics data from patients unravels regulatory mechanisms of diseases and trained immunity

Contact

Prof. Dr. Yang Li: Yang.Li@helmholtz-hzi.de (Group Leader) Zhenhua.Zhang@helmholtz-hzi.de Wenchao.Li@helmholtz-hzi.de